Utilizing Pseudo-Random Patterns for Eye Tracking in Augmented or Virtual Reality Systems

1. An eye tracking device to be used in a head-worn virtual or augmented reality device, comprising: a virtual content generation subsystem configured to render virtual contents to a user; a plurality of light sources comprising multiple groups of light sources configured to illuminate one eye of the user at least with a pseudorandom pattern, wherein the pseudorandom pattern that comprises a patterned code generated at least by pseudo-randomly varying at least one parameter of one or more groups of the multiple groups of light sources while leaving the at least one parameter of one or more remaining groups of the multiple groups unchanged in a plurality of time slices; an eye tracking device positioned in relation to the one eye of the user and configured to detect one or more characteristics pertaining to an interaction between the light from the one or more groups of the multiple groups of the plurality of light sources and the one eye based in part or in whole upon the pseudorandom pattern; and a processor operatively coupled to the eye tracking device to: determine an eye model representing the one eye of the user with two circular geometric shapes; determine a plurality of eye pointing vectors with the eye model based at least in part upon the one or more characteristics pertaining to the interaction; and determine a movement or a pose of the one eye based at least in part on the plurality of eye pointing vectors and apply the movement or the pose of the one eye as a calculated movement or calculated pose to both eyes.

2. The eye-tracking device of claim 1 , wherein the one or more characteristics pertain to light reflected back from the one eye, and the one or more characteristics pertaining to the interaction are determined with at least the plurality of vector distances, rather than ray traces.

3. The eye-tracking device of claim 1 , wherein the one or more characteristics pertain to one or more reflections of objects from a structure of the user's eyes.

4. The eye-tracking device of claim 1 , wherein the at least one parameter includes a length of emission.

5. The eye-tracking device of claim 4 , wherein the eye tracking device is configured to detect first light emitted from the one or more groups of the multiple groups and reflected from the at least one eye from second light emitted from one or more ambient light sources and reflected from the at least one eye.

6. The eye-tracking device of claim 4 , wherein the at least one parameter corresponds to a length of emission of at least one light source of the plurality of light sources.

7. The eye-tracking device of claim 1 , wherein the plurality of light sources are configured to emit the light in a predetermined pattern.

8. The eye-tracking device of claim 1 , wherein the eye tracking device comprises a photodiode.

9. The eye-tracking device of claim 1 , wherein the processor is configured to determine the movement or the pose based at least in part on a known distance of the at least one eye from the eye tracking device and the plurality of light sources.

10. The eye-tracking device of claim 1 , wherein the processor is further configured to determine one or more time of flight signals based on the light emitted by the plurality of light sources and signals from the at least one eye collected by the eye tracking device.

11. A machine implemented method for tracking movements or poses of eyes with a virtual or augmented reality device, comprising: rendering virtual contents to a user with the virtual or augmented reality device; emitting light with a plurality of light sources comprising multiple groups of light sources according to a pseudorandom pattern that comprises a patterned code generated at least by varying at least one parameter of one or more groups of the multiple groups of light sources while leaving the at least one emitted light parameter of one or more remaining groups of the multiple groups unchanged according to a plurality of time slices; detecting one or more characteristics pertaining to an interaction between the light emitted from the plurality of light sources and the one eye of the user in response to the virtual contents based in part or in whole upon the pseudorandom pattern; and determining, at a microprocessor, a movement or a pose of the one eye of the user based at least in part upon the one or more characteristics, wherein determining the movement or the pose comprises: determining an eye model representing the one eye of the user with two circular geometric shapes; determining a plurality of eye pointing vectors with the eye model based at least in part upon the one or more characteristics pertaining to the interaction; and determining a movement or a pose of the one eye based at least in part on the plurality of eye pointing vectors and apply the movement or the pose of the one eye as a calculated movement or calculated pose to both eyes.

12. The machine implemented method of claim 11 , further comprising: illuminating the one eye of the user with the light emitted by at least one light source of the plurality of light sources; and tracking the movement or the pose of the one eye of the user by using at least pseudorandom noise.

13. The machine implemented method of claim 11 , further comprising: receiving light signals from the one eye with an eye tracking device; and identifying one or more Purkinje images from a structure of the one eye of the user.

14. The machine implemented method of claim 13 , further comprising: imposing a pattern on the light signals from the one eye of the user at least by varying one or more parameters of the light emitted by at least one light source of the plurality of light sources according to the pseudorandom pattern, wherein the at least one parameter of the light comprises on-off states of the multiple groups of one or more light sources according to one or more time slices of the plurality of time slices; the pseudorandom pattern includes switching on and switching off the plurality of light sources one at a time according to the one or more time slices.

15. The machine implemented method of claim 13 , further comprising: generating the patterned code according to the plurality of time slices; and generating one or more time of flight signals at least by correlating the light signals received by the eye tracking device from the one eye of the user.

16. The machine implemented method of claim 11 , further comprising: identifying first known geometric characteristics of the plurality of light sources; determining first distances between the plurality of light sources and the at least one eye; identifying one or more second known geometric characteristics of the eye tracking device; determining one or more second distances between the eye tracking device and the one eye; and identifying one or more third known geometric characteristics of the one eye of the user.

17. The machine implemented method of claim 16 , identifying the one or more third known geometric characteristics of the at least one eye further comprising: representing the one eye of the user as two overlapping geometric shapes; determining a center of rotation of the one eye by using the two overlapping geometric shapes and a third known geometric characteristic of a cornea of the one or more third known geometric characteristics; and determining a vector distance based in part or in whole upon a correlation between the light signals from the one eye and the light emitted by the plurality of light sources.

18. The machine implemented method of claim 16 , further comprising: determining a sum of vectors with the one or more third known geometric characteristics of the one eye based in part or in whole the first distances and the second distances; determining an eye pointing vector for the at least one eye of the user without using cameras; and detecting the one or more characteristics pertaining to the interaction of the light, detecting the one or more characteristics comprising at least one of: detecting an extent of backscattered light detected by the eye tracking device comprising at least one photodiodes; or detecting a direction of the backscattered light.

19. The machine implemented method of claim 11 , further comprising: measuring one or more interaction parameters of the interaction at the eye tracking device; and determining the movement or the pose of the one eye at least by extrapolating one or more movement or pose characteristics pertaining to the movement or the pose of the one eye.